3 papers
cs.LG2021
Semi-Supervised Clustering with Inaccurate Pairwise Annotations
Daniel Gribel, Michel Gendreau, Thibaut Vidal
Pairwise relational information is a useful way of providing partial supervision in domains where class labels are difficult to acquire. This work presents a clustering model that…
cs.SI2020
Assortative-Constrained Stochastic Block Models
Daniel Gribel, Thibaut Vidal, Michel Gendreau
Stochastic block models (SBMs) are often used to find assortative community structures in networks, such that the probability of connections within communities is higher than in be…
cs.LG2018
HG-means: A scalable hybrid genetic algorithm for minimum sum-of-squares clustering
Daniel Gribel, Thibaut Vidal
Minimum sum-of-squares clustering (MSSC) is a widely used clustering model, of which the popular K-means algorithm constitutes a local minimizer. It is well known that the solution…